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Gender Equality: Exploring aesthetic programming as a way to increase diversity and shape inclusivity in our digital society

Gender Equality: Exploring aesthetic programming as a way to...

引用

ieee International Humanitarian Technology conference (ieee IHTC)

作者： Carroll, Fiona Faruque, Rumana Cardiff Met Univ Cardiff Sch Technol Llandaff CampusWestern Ave Cardiff CF5 2YB Wales

ISBN: (纸本)9781665449250

Women are still globally under-represented in IT. Despite efforts over the last twenty years to narrow the gender gap in STEM education, a large imbalance still persists in many countries throughout the world. This paper discusses the current global gender gap in STEM. It presents an initial study with a range of primary school pupils in Wales, UK that explored a new mode of aesthetic problem solving in order to teach programming. The findings show that this aesthetic approach was successful in engaging all genders in programming. The approach not only introduced programming practically and creatively but also highlighted the importance of the problem being solved and around this cultivating an open space for pupils to discuss, reflect and grow a gender-neutral computational culture. Indeed, to create an equitable digital society, we need to break down the existing barriers and find new ways to tackle the STEM gender gap in order to build a stronger and a fairer digital world.

关键词： Aesthetic programming girls in IT equitable digital society inclusivity

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Multiscale Empirical Analysis of Software network Evolution 21

Multiscale Empirical Analysis of Software Network Evolution

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21st ieee International conference on Software Quality, Reliability and Security (QRS)

作者： Gou, Xiaodong Fan, Long Zhao, Li Shao, Qi Bian, Chong Yang, Shunkun Beihang Univ Sch Reliabil & Syst Engn Beijing Peoples R China China Shipbldg Ind Syst Engn Res Inst Beijing Peoples R China Sichuan Commun Surveying & Design Inst Co Ltd Chengdu Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing Peoples R China

ISBN: (纸本)9781665478366

Understanding the evolution of the complex software system during the updates is useful for a variety of software development and maintenance activities, however, few works have studied the multiscale evolution characteristics of software in different programming languages from the perspective of the network. In this paper, we investigate the evolution of twelve open source software in ten programming languages from three scales: macroscopic, mesoscopic and microscopic. Analysis results show some interesting observations, for example, the in-degree distributions exhibit the coexistence of power-law distribution and lognormal distribution, and may even change to each other in evolution process. In addition, software does not always become more orderly and modular during the update process, but the software in different programming languages has similarities in microstructure. What's more, there are strong correlations between the software's macroscopic, mesoscopic, and microscopic properties and the size of the software, while there are no significant correlations between these three properties. The analysis and discussion in this paper can provide useful insights for software developers to understand the complexity of software.

关键词： multiple programming languages software evolution complex network

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Distributed and Heterogeneous SAR Backprojection with Halide

Distributed and Heterogeneous SAR Backprojection with Halide

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ieee High Performance Extreme Computing conference (HPEC)

作者： Imes, Connor Li, Tzu-Mao Glines, Mark Khan, Rishi Walters, John Paul Univ Southern Calif Informat Sci Inst Los Angeles CA 90007 USA Univ Calif San Diego La Jolla CA 92093 USA Extreme Scale Solut New Castle DE USA MIT CSAIL Cambridge MA USA

ISBN: (纸本)9781665423694

Writing efficient, scalable, and portable HPC synthetic aperture radar (SAR) applications is increasingly challenging due to the growing diversity and heterogeneity in distributed systems. Considerable developer and computational resources are often spent to port applications to new HPC platforms and architectures, which is both time consuming and expensive. Domain-specific languages have been shown to be highly productive for development effort, but additionally achieving both scalable computational efficiency and platform portability remains challenging. The Halide programming language is both productive and efficient for dense data processing, supports common CPU architectures and heterogeneous resources like GPUs, and has previously been extended for distributed processing. We propose to use a distributed Halide implementation for scalable and heterogeneous HPC SAR processing. We implement a backprojection algorithm for SAR image reconstruction and demonstrate scalability on the OLCF Summit supercomputer up to 1,024 compute nodes (43,008 cores, each with 4 hardware threads) with a large 32,768x32,768 dataset, and up to 8 distributed GPUs with a 8,192x 8,192 dataset. Our results show excellent scaling and portability to heterogeneous resources, and motivate additional improvements in Halide to better support distributed high-performance signal processing.

关键词： parallel programming high performance computing synthetic aperture radar

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Data Race Detection Using Large Language Models

Data Race Detection Using Large Language Models

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2023 International conference on High Performance Computing, network, Storage, and Analysis, SC Workshops 2023

作者： Chen, Le Ding, Xianzhong Emani, Murali Vanderbruggen, Tristan Lin, Pei-Hung Liao, Chunhua Iowa State University AmesIA United States Lawrence Livermore National Laboratory LivermoreCA United States University of California Merced MercedCA United States Argonne National Laboratory LemontIL United States

ISBN: (纸本)9798400707858

Large language models (LLMs) are demonstrating significant promise as an alternate strategy to facilitate analyses and optimizations of high-performance computing programs, circumventing the need for resource-intensive manual tool creation. In this paper, we explore a novel LLM-based data race detection approach combining prompting engineering and fine-tuning techniques. We create a dedicated dataset named DRB-ML, which is derived from DataRaceBench, with fine-grain labels showing the presence of data race pairs and their associated variables, line numbers, and read/write information. DRB-ML is then used to evaluate representative LLMs and fine-tune open-source ones. Our experiment shows that LLMs can be a viable approach to data race detection. However, they still cannot compete with traditional data race detection tools when we need detailed information about variable pairs causing data races. © 2023 Owner/Author.

关键词： Application programming interfaces (API)

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Finding Anomalies in Scratch Assignments 43

Finding Anomalies in Scratch Assignments

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43rd ieee/ACM International conference on Software Engineering - Joint Track on Software Engineering Education and Training (ICSE-JSEET) / ieee/ACM 43rd International conference on Software Engineering -Software Engineering in Society (ICSE-SEIS)

作者： Koerber, Nina Geldreich, Katharina Stahlbauer, Andreas Fraser, Gordon Univ Passau Passau Germany Tech Univ Munich Munich Germany

ISBN: (纸本)9780738133201

In programming education, teachers need to monitor and assess the progress of their students by investigating the code they write. Code quality of programs written in traditional programming languages can be automatically assessed with automated tests, verification tools, or linters. In many cases these approaches rely on some form of manually written formal specification to analyze the given programs. Writing such specifications, however, is hard for teachers, who are often not adequately trained for this task. Furthermore, automated tool support for popular block-based introductory programming languages like SCRATCH is lacking. Anomaly detection is an approach to automatically identify deviations of common behavior in datasets without any need for writing a specification. In this paper, we use anomaly detection to automatically find deviations of SCRATCH code in a classroom setting, where anomalies can represent erroneous code, alternative solutions, or distinguished work. Evaluation on solutions of different programming tasks demonstrates that anomaly detection can successfully be applied to tightly specified as well as open-ended programming tasks.

关键词： Anomaly Detection Scratch Block-Based programming Program Analysis Teaching

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NetVerify 2021-network Verification Workshop 29

NetVerify 2021-Network Verification Workshop

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29th ieee International conference on network Protocols (ICNP)

作者： Jayaraman, Karthick Yang, Hongkun Microsoft Azure Networking Redmond WA 98052 USA Google Cloud Platform Mountain View CA USA

ISBN: (纸本)9781665441315

Preserving the availability and trustworthiness of computer networks continues to be an open challenge. Traditionally, we used expert engineers to manage all aspects of the network. This approach is not viable for large-scale networks. On one hand, we have cloud networks that comprise several hundreds of thousands of network devices that interconnect several million servers. New advances such as programmable network devices further magnify the complexity - we now also have churn in the data plane in addition to the control plane. On the other hand, we have enterprises migrating to the cloud and deploying virtual networks at scale. Managing both kind of networks require solving the same challenges such as intent specification, correct-by-construction translation to configurations, re-mediating drift, and finally ensuring the safety of changes. Solving these challenges requires a multi-pronged approach. NetVerify will create interdisciplinary forum to foster interactions between researchers and practitioners from fields such as networking, security, formal methods, programming languages, and machine learning. The workshop program is designed to stimulate discussions to both advance the science of network verification and influence adoption.

关键词： network security

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Distributed Out-of-Memory SVD on CPU/GPU architectures

Distributed Out-of-Memory SVD on CPU/GPU Architectures

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ieee High Performance Extreme Computing Virtual conference (HPEC)

作者： Boureima, Ismael Bhattarai, Manish Eren, Maksim E. Solovyev, Nick Djidjev, Hristo Alexandrov, Boian S. LANL Div Theoret Los Alamos NM 87545 USA IICT Sofia Bulgaria

ISBN: (数字)9781665497862

ISBN: (纸本)9781665497862

We propose an efficient, distributed, out-of-memory implementation of the truncated singular value decomposition (t-SVD) for heterogeneous high performance computing (HPC) systems. Various implementations of SVD have been proposed, with most only estimate the singular values as the estimation of the singular vectors can significantly increase the time and memory complexity of the algorithm. In this work, we propose an implementation of SVD based on the power method, which is a truncated singular values and singular vectors estimation method. Memory utilization bottlenecks in the power method used to decompose a matrix A are typically associated with the computation of the Gram matrix A(T) A, which can be significant when A is large and dense, or when A is super-large and sparse. The proposed implementation is optimized for out-of-memory problems where the memory required to factorize a given matrix is greater than the available GPU memory. We reduce the memory complexity of A(T) A by using a batching strategy where the intermediate factors are computed block by block, and we hide I/O latency associated with both host-to-device (H2D) and device-to-host (D2H) batch copies by overlapping each batch copy with compute using CUDA streams. Furthermore, we use optimized NCCL based communicators to reduce the latency associated with collective communications (both intra-node and inter-node). In addition, sparse and dense matrix multiplications are significantly accelerated with GPU cores (or tensors cores when available), resulting in an implementation with good scaling. We demonstrate the scalability of our distributed out of core SVD algorithm to successfully decompose dense matrix of size 1TB and sparse matrix of 1e-6 sparsity with size of 128 PB in dense format.

关键词： SVD out-of-memory latent features data compression distributed processing parallel programming big data heterogeneous HPC systems GPU CUDA NCCL cupy

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OP4T: Bringing Advanced network Packet Timestamping into the Field 35

OP4T: Bringing Advanced Network Packet Timestamping into the...

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35th International conference on Information networking (ICOIN)

作者： Hawari, Mohammed Clausen, Thomas Cisco Syst Issy Les Moulineaux France Ecole Polytech Paris France

ISBN: (纸本)9781728191010

Because it is very bursty, the microsecond-scale temporal behaviour of network traffic in data-centres is challenging to measure and understand. To bring observability into data-centre networks, this paper introduces the open Platform for Programmable Precise Packet Timestamping (OP4T), a hardware architecture, targeting Field-Programmable Gateway Arrays (FPGAs), integrated into data-centre servers as a Smart network Interface Card (SmartNIC), and flexible enough to enable advanced latency diagnosis. In this paper, OP4T is specified, and an open-source implementation of that architecture is proposed, targeting the NetFPGA SUME prototyping board. By leveraging the P4 programming language, and partial reconfiguration, that open-source implementation is experimentally shown to enable in-band, precise packet timestamping, without sacrificing the achievable throughput. As an illustration, OP4T is shown to be usable to measure fine-grained properties of a software packet forwarder, e.g., packet batching.

关键词： Gateways (computer networks)

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Docmarking: Real-Time Screen-Cam Robust Document Image Watermarking

Docmarking: Real-Time Screen-Cam Robust Document Image Water...

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2022 Ivannikov open conference, ISPRAS 2022

作者： Yakushev, Aleksey Markin, Yury Obydenkov, Dmitry Frolov, Alexander Fomin, Stas Akopyan, Manuk Kozachok, Alexander Gaynov, Arthur Ivannikov Institute for System Programming of the Ras Moscow Russia Russian Federation Security Guard Service Federal Academy Oryol Russia Ministry of Defence of the Russian Federation Moscow Russia

ISBN: (纸本)9798350398533

This paper focuses on investigation of confidential documents leaks in the form of screen photographs. Proposed approach does not try to prevent leak in the first place but rather aims to determine source of the leak. Method works by applying on the screen a unique identifying watermark as semi-transparent image that is almost imperceptible for human eyes. Watermark image is static and stays on the screen all the time thus watermark present on every captured photograph of the screen. The key components of the approach are three neural networks. The first network generates an image with embedded message in a way that this image is almost invisible when displayed on the screen. The other two neural networks are used to retrieve embedded message with high accuracy. Developed method was comprehensively tested on different screen and cameras. Test results showed high efficiency of the proposed approach. © 2022 ieee.

关键词： Image watermarking

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Proceedings - 2022 23rd ACIS International Summer Virtual conference on Software Engineering, Artificial Intelligence, networking and Parallel/Distributed Computing, SNPD-Summer 2022

Proceedings - 2022 23rd ACIS International Summer Virtual Co...

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23rd ACIS International Summer Virtual conference on Software Engineering, Artificial Intelligence, networking and Parallel/Distributed Computing, SNPD-Summer 2022

ISBN: (纸本)9798350396379

The proceedings contain 27 papers. The topics discussed include: Tetris: automatic UAF exploit generation by manipulating layout based on reactivated paths;artificial neural network for processing fingerprint image noise;facial expression intensity estimation considering change characteristic of facial feature values for each facial expression;developing a gamification method based on motivation subscales for lifelogging applications;preliminary study of reasoning existing projects' descriptions based on classname word elements;construction and evaluation of a speech emotion classifier using LSTM;concurrency control program generation in genetic programming considering depth of the program tree;reconfiguration cost for reconfigurable computing architectures;and parallel binary search tree construction inspired by thread-level speculation.

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